Causality estimates among brain cortical areas by Partial Directed Coherence: simulations and application to real data

The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. Among various methods established during the years, the Partial Directed Coherence (PDC) is a frequency-domain approach to this problem, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. In this paper we propose the use of the PDC method on cortical signals estimated from high resolution EEG recordings, a non invasive method which exhibits a higher spatial resolution than conventional cerebral electromagnetic measures. The principle contributions of this work are the results of a simulation study, testing the performances of PDC, and a statistical analysis (via the ANOVA, analysis of variance) of the influence of different levels of Signal to Noise Ratio and temporal length, as they have been systematically imposed on simulated signals. An application to high resolution EEG recordings during a foot movement is also presented

Scale-free brain functional networks

Functional magnetic resonance imaging (fMRI) is used to extract {\em functional networks} connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that: (a) the distribution of functional connections, and the probability of finding a link vs. distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small world networks, reflect important functional information about brain states.Comment: 4 pages, 5 figures, 2 table

D\u27Amico Risk Stratification Correlates with Degree of Suspicion of Prostate Cancer on Multiparametric Magnetic Resonance Imaging.

PURPOSE: We determined whether there is a correlation between D\u27Amico risk stratification and the degree of suspicion of prostate cancer on multiparametric magnetic resonance imaging based on targeted biopsies done with our electromagnetically tracked magnetic resonance imaging/ultrasound fusion platform. MATERIALS AND METHODS: A total of 101 patients underwent 3 Tesla multiparametric magnetic resonance imaging of the prostate, consisting of T2, dynamic contrast enhanced, diffusion weighted and spectroscopy images in cases suspicious for or with a diagnosis of prostate cancer. All prostate magnetic resonance imaging lesions were then identified and graded by the number of positive modalities, including low-2 or fewer, moderate-3 and high-4 showing suspicion on multiparametric magnetic resonance imaging. The biopsy protocol included standard 12-core biopsy, followed by real-time magnetic resonance imaging/ultrasound fusion targeted biopsies of the suspicious magnetic resonance lesions. Cases and lesions were stratified by the D\u27Amico risk stratification. RESULTS: In this screening population 90.1% of men had a negative digital rectal examination. Mean±SD age was 62.7±8.3 years and median prostate specific antigen was 5.8 ng/ml. Of the cases 54.5% were positive for cancer on protocol biopsy. Chi-square analysis revealed a statistically significant correlation between magnetic resonance suspicion and D\u27Amico risk stratification (p CONCLUSIONS: Our data support the notion that using multiparametric magnetic resonance prostate imaging one may assess the degree of risk associated with magnetic resonance visible lesions in the prostate

Early, transient depletion of plasmacytoid dendritic cells ameliorates autoimmunity in a lupus model

Plasmacytoid dendritic cells (pDCs) have long been implicated in the pathogenesis of lupus. However, this conclusion has been largely based on a correlative link between the copious production of IFN-α/β by pDCs and the IFN-α/β “signature” often seen in human lupus patients. The specific contribution of pDCs to disease in vivo has not been investigated in detail. For this reason, we generated a strain of BXSB lupus-prone mice in which pDCs can be selectively depleted in vivo. Early, transient ablation of pDCs before disease initiation resulted in reduced splenomegaly and lymphadenopathy, impaired expansion and activation of T and B cells, reduced antibodies against nuclear autoantigens and improved kidney pathology. Amelioration of pathology coincided with decreased transcription of IFN-α/β–induced genes in tissues. PDC depletion had an immediate impact on the activation of immune cells, and importantly, the beneficial effects on pathology were sustained even though pDCs later recovered, indicating an early pDC contribution to disease. Together, our findings demonstrate a critical function for pDCs during the IFN-α/β–dependent initiation of autoimmune lupus and point to pDCs as an attractive therapeutic target for the treatment of SLE

Prodrug Strategy for PSMA-targeted Delivery of TGX-221 to Prostate Cancer Cells

TGX-221 is a potent, selective, and cell membrane permeable inhibitor of the PI3K p110β catalytic subunit. Recent studies showed that TGX-221 has anti-proliferative activity against PTEN-deficient tumor cell lines including prostate cancers. The objective of this study was to develop an encapsulation system for parenterally delivering TGX-221 to the target tissue through a prostate-specific membrane aptamer (PSMAa10) with little or no side effects. In this study, PEG-PCL micelles were formulated to encapsulate the drug, and a prodrug strategy was pursued to improve the stability of the carrier system. Fluorescence imaging studies demonstrated that the cellular uptake of both drug and nanoparticles were significantly improved by targeted micelles in a PSMA positive cell line. The area under the plasma concentration time curve of the micelle formulation in nude mice was 2.27-fold greater than the naked drug, and the drug clearance rate was 17.5-fold slower. These findings suggest a novel formulation approach for improving site-specific drug delivery of a molecular-targeted prostate cancer treatment

T- and B-cell responses to multivalent prime-boost DNA and viral vectored vaccine combinations against hepatitis C virus in non-human primates.

Immune responses against multiple epitopes are required for the prevention of hepatitis C virus (HCV) infection, and the progression to phase I trials of candidates may be guided by comparative immunogenicity studies in non-human primates. Four vectors, DNA, SFV, human serotype 5 adenovirus (HuAd5) and Modified Vaccinia Ankara (MVA) poxvirus, all expressing hepatitis C virus Core, E1, E2 and NS3, were combined in three prime-boost regimen, and their ability to elicit immune responses against HCV antigens in rhesus macaques was explored and compared. All combinations induced specific T-cell immune responses, including high IFN-γ production. The group immunized with the SFV+MVA regimen elicited higher E2-specific responses as compared with the two other modalities, while animals receiving HuAd5 injections elicited lower IL-4 responses as compared with those receiving MVA. The IFN-γ responses to NS3 were remarkably similar between groups. Only the adenovirus induced envelope-specific antibody responses, but these failed to show neutralizing activity. Therefore, the two novel regimens failed to induce superior responses as compared with already existing HCV vaccine candidates. Differences were found in response to envelope proteins, but the relevance of these remain uncertain given the surprisingly poor correlation with immunogenicity data in chimpanzees, underlining the difficulty to predict efficacy from immunology studies.This work was supported by European Union contract QLK2-CT-1999- 00356, by the Biomedical Primate Research Centre, The Netherlands, and by the Swedish Research Council. We are grateful to Alexander van den Berg for technical assistance with the ICS, to our colleagues from Animal Science Department for technical assistance and expert care of the macaques, to the participants of the European HCVacc Cluster who provided help and support, and to Thomas Darton (Oxford Vaccine Group, UK) for input and advice on the manuscript. Christine Rollier is an Oxford Martin fellow and a Jenner Insitute Investigator.This is the author accepted manuscript. The final version is available from Nature Publishing Group at https://doi.org/10.1038/gt.2016.55

Boolean dynamics revisited through feedback interconnections

Boolean models of physical or biological systems describe the global dynamics of the system and their attractors typically represent asymptotic behaviors. In the case of large networks composed of several modules, it may be difficult to identify all the attractors. To explore Boolean dynamics from a novel viewpoint, we will analyse the dynamics emerging from the composition of two known Boolean modules. The state transition graphs and attractors for each of the modules can be combined to construct a new asymptotic graph which will (1) provide a reliable method for attractor computation with partial information; (2) illustrate the differences in dynamical behavior induced by the updating strategy (asynchronous, synchronous, or mixed); and (3) show the inherited organization/structure of the original network’s state transition graph.publishe

Review of the methods of determination of directed connectivity from multichannel data

The methods applied for estimation of functional connectivity from multichannel data are described with special emphasis on the estimators of directedness such as directed transfer function (DTF) and partial directed coherence. These estimators based on multivariate autoregressive model are free of pitfalls connected with application of bivariate measures. The examples of applications illustrating the performance of the methods are given. Time-varying estimators of directedness: short-time DTF and adaptive methods are presented

Assembling a global database of child pneumonia studies to inform WHO pneumonia management algorithm: methodology and applications

BACKGROUND: The existing World Health Organization (WHO) pneumonia case management guidelines rely on clinical symptoms and signs for identifying, classifying, and treating pneumonia in children up to 5 years old. We aimed to collate an individual patient-level data set from large, high-quality pre-existing studies on pneumonia in children to identify a set of signs and symptoms with greater validity in the diagnosis, prognosis, and possible treatment of childhood pneumonia for the improvement of current pneumonia case management guidelines. METHODS: Using data from a published systematic review and expert knowledge, we identified studies meeting our eligibility criteria and invited investigators to share individual-level patient data. We collected data on demographic information, general medical history, and current illness episode, including history, clinical presentation, chest radiograph findings when available, treatment, and outcome. Data were gathered separately from hospital-based and community-based cases. We performed a narrative synthesis to describe the final data set. RESULTS: Forty-one separate data sets were included in the Pneumonia Research Partnership to Assess WHO Recommendations (PREPARE) database, 26 of which were hospital-based and 15 were community-based. The PREPARE database includes 285 839 children with pneumonia (244 323 in the hospital and 41 516 in the community), with detailed descriptions of clinical presentation, clinical progression, and outcome. Of 9185 pneumonia-related deaths, 6836 (74%) occurred in children <1 year of age and 1317 (14%) in children aged 1-2 years. Of the 285 839 episodes, 280 998 occurred in children 0-59 months old, of which 129 584 (46%) were 2-11 months of age and 152 730 (54%) were males. CONCLUSIONS: This data set could identify an improved specific, sensitive set of criteria for diagnosing clinical pneumonia and help identify sick children in need of referral to a higher level of care or a change of therapy. Field studies could be designed based on insights from PREPARE analyses to validate a potential revised pneumonia algorithm. The PREPARE methodology can also act as a model for disease database assembly